Senior Data Scientist, Knowledge Layer

TRM Labs

9d • $180,000 - $210,000 • Remote

About The Position

TRM Labs is hiring a Senior Data Scientist for its Knowledge Layer team, which extracts, structures, and analyzes knowledge from large-scale unstructured data. The team works across knowledge graphs, entity resolution, graph extraction, and graph analytics to power TRM’s intelligence products. The role brings practical machine learning and data science expertise to a team with strong backend and graph engineering capabilities.

The position spans the full machine learning lifecycle, from model selection and experimentation through production deployment. The successful candidate will develop machine learning solutions for knowledge extraction, graph-based learning, entity resolution, and relationship discovery; collaborate with backend and graph engineers to integrate models into services and APIs; and contribute to knowledge graph and ontology design. The role also includes exploratory data analysis, evaluation and iteration of ML components, and helping establish applied ML practices for the team.

The role requires participation in in-person R&D work weeks, typically one to two times per quarter, at a TRM hub or another designated location. Work weeks may be scheduled with as little as 14 days’ notice, and additional travel may be needed based on team and cross-functional needs. TRM coordinates and covers approved travel, lodging, and workspace. The position may be eligible for TRM’s equity plan.

Requirements

• At least 5 years of experience in data science, machine learning engineering, or applied machine learning.
• Strong programming experience in Python.
• Hands-on experience building, training, or deploying machine learning models in production.
• Familiarity with NLP or information extraction techniques, such as named entity recognition, text classification, or embedding-based approaches.
• Solid software engineering fundamentals, including building and maintaining APIs or services.
• Ability to translate ambiguous problem spaces into practical machine learning solutions.
• Strong communication skills and comfort collaborating with engineers across disciplines.

Nice To Haves

• Experience or strong interest in knowledge graphs, graph data, or graph-based machine learning.

Responsibilities

• Design, build, and productionize machine learning models for knowledge extraction from unstructured data, including named entity recognition and entity linking.
• Develop models and approaches for graph-based learning and inference.
• Build solutions for entity resolution and relationship discovery.
• Evaluate and leverage existing machine learning models and frameworks to solve real-world problems efficiently.
• Partner with backend and graph engineers to integrate machine learning models into production services and APIs.
• Contribute to the design and evolution of knowledge graphs and ontologies.
• Perform exploratory data analysis to inform modeling decisions and system design.
• Own machine learning components end-to-end, including experimentation, evaluation, deployment, and iteration.
• Help shape best practices for applied machine learning within the Knowledge Layer team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed